Causal inference with (partially) independent shocks and structural signals on the global crude oil market

Christian M. Hafner (donatien.hainaut@uclouvain.be), Helmut Herwartz and Shu Wang
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Christian M. Hafner: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2023004, LIDAM Discussion Papers ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: Independent component analysis has recently become a promising data-based approach to detect structural relations in multivariate dynamic systems in cases when apriori knowledge about causal patterns are scant. This paper suggests a kernel-based ML estimation that is largely agnostic with regard to the distributional features of the structural origins of data variation and enables causal analysis under the assumption of having only a subset of independent shocks. In an empirical application to the global oil market model of Kilian (2009) we illustrate the benefits of allowing for an unmodelled higher-order dependence among the oil supply and speculative oil demand shocks.

Keywords: Structural VAR; structural MGARCH; Independent component analysis (search for similar items in EconPapers)
JEL-codes: C14 C32 Q43 (search for similar items in EconPapers)
Pages: 48
Date: 2023-01-25
New Economics Papers: this item is included in nep-ecm, nep-ene and nep-ets
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Citations: View citations in EconPapers (2)

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